Government agencies typically need to take potential risks of disclosure into account whenever they publish statistics based on their data or give external researchers access to collected data. In this context, the promise of formal privacy guarantees offered by concepts such as differential privacy seems to be the panacea enabling the agencies to quantify and control the privacy loss incurred by any data release exactly. Nevertheless, despite the excitement in academia and industry, most agencies -- with the prominent exception of the U.S. Census Bureau -- have been reluctant to even consider the concept for their data release strategy. This paper discusses potential reasons for this. We argue that the requirements for implementing differential privacy approaches at government agencies are often fundamentally different from the requirements in industry. This raises many challenges and questions that still need to be addressed before the concept can be used as an overarching principle when sharing data with the public. The paper does not offer any solutions to these challenges. Instead, we hope to stimulate some collaborative research efforts, as we believe that many of the problems can only be addressed by interdisciplinary collaborations.
翻译:通常,政府各机构在公布基于其数据的统计数据或让外部研究人员查阅所收集的数据时,需要考虑到披露的潜在风险。在这方面,不同隐私概念所提供的正式隐私保障的许诺似乎是灵丹妙药,使各机构能够精确地量化和控制任何数据发布造成的隐私损失。然而,尽管学术界和工业界感到兴奋,但大多数机构 -- -- 除美国人口普查局以外 -- -- 都不愿意考虑数据发布战略的概念。本文讨论了这样做的潜在原因。我们争辩说,政府机构采用不同隐私方法的要求往往与行业的要求有根本的不同。这提出了许多挑战与问题,在与公众分享数据时,在将这一概念作为首要原则使用之前,还需要解决这些挑战和问题。该文件没有为这些挑战提供任何解决办法。相反,我们希望激发一些合作研究努力,因为我们认为,许多问题只能通过跨学科合作来解决。